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Title: Machine-learning-based jet momentum reconstruction in heavy-ion collisions

Authors:
;
Publication Date:
Sponsoring Org.:
USDOE Office of Science (SC), Nuclear Physics (NP) (SC-26)
OSTI Identifier:
1546257
Grant/Contract Number:  
SC004168; AC05-00OR22725
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Physical Review C
Additional Journal Information:
Journal Name: Physical Review C Journal Volume: 99 Journal Issue: 6; Journal ID: ISSN 2469-9985
Publisher:
American Physical Society
Country of Publication:
United States
Language:
English

Citation Formats

Haake, Rüdiger, and Loizides, Constantin. Machine-learning-based jet momentum reconstruction in heavy-ion collisions. United States: N. p., 2019. Web. doi:10.1103/PhysRevC.99.064904.
Haake, Rüdiger, & Loizides, Constantin. Machine-learning-based jet momentum reconstruction in heavy-ion collisions. United States. doi:10.1103/PhysRevC.99.064904.
Haake, Rüdiger, and Loizides, Constantin. Mon . "Machine-learning-based jet momentum reconstruction in heavy-ion collisions". United States. doi:10.1103/PhysRevC.99.064904.
@article{osti_1546257,
title = {Machine-learning-based jet momentum reconstruction in heavy-ion collisions},
author = {Haake, Rüdiger and Loizides, Constantin},
abstractNote = {},
doi = {10.1103/PhysRevC.99.064904},
journal = {Physical Review C},
number = 6,
volume = 99,
place = {United States},
year = {2019},
month = {6}
}

Journal Article:
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This content will become publicly available on June 16, 2020
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Works referenced in this record:

Random Forests
journal, January 2001